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import gradio as gr |
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from moviepy.editor import * |
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from share_btn import community_icon_html, loading_icon_html, share_js |
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caption = gr.Blocks.load(name="spaces/SRDdev/Image-Caption") |
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audio_gen = gr.Blocks.load(name="spaces/haoheliu/audioldm-text-to-audio-generation") |
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def infer(image_input): |
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cap = caption(image_input, fn_index=0) |
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sound = audio_gen(cap, 5, 2.5, 45, 3, fn_index=0) |
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FILETOCONVERT = AudioFileClip(sound) |
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FILETOCONVERT.write_audiofile("audio.wav") |
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FILETOCONVERT.close() |
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return gr.Textbox.update(value=cap, visible=True), "audio.wav", gr.Group.update(visible=True) |
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title = """ |
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<div style="text-align: center; max-width: 700px; margin: 0 auto;"> |
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<div |
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style=" |
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display: inline-flex; |
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align-items: center; |
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gap: 0.8rem; |
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font-size: 1.75rem; |
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" |
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> |
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<h1 style="font-weight: 900; margin-bottom: 7px; margin-top: 5px;"> |
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Image to Sound Effect |
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</h1> |
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</div> |
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<p style="margin-bottom: 10px; font-size: 94%"> |
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Convert an image to corresponding sound effect through gpt2 image captioning & AudioLDM |
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</p> |
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</div> |
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""" |
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article = """ |
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<div class="footer"> |
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<p> |
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Follow <a href="https://twitter.com/fffiloni" target="_blank">Sylvain Filoni</a> for future updates π€ |
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</p> |
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</div> |
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""" |
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with gr.Blocks(css="style.css") as demo: |
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with gr.Column(elem_id="col-container"): |
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gr.HTML(title) |
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input_img = gr.Image(type="filepath", elem_id="input-img") |
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caption_output = gr.Textbox(label="Caption", lines=1, visible=False, elem_id="text-caption") |
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sound_output = gr.Audio(label="Result", elem_id="sound-output") |
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generate = gr.Button("Generate SFX from Image") |
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with gr.Group(elem_id="share-btn-container", visible=False) as share_group: |
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community_icon = gr.HTML(community_icon_html) |
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loading_icon = gr.HTML(loading_icon_html) |
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share_button = gr.Button("Share to community", elem_id="share-btn") |
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gr.HTML(article) |
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generate.click(infer, inputs=[input_img], outputs=[caption_output, sound_output, share_group], api_name="i2fx") |
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share_button.click(None, [], [], _js=share_js) |
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demo.queue(max_size=32, concurrency_count=20).launch() |
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